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| Models | Description |
| Boolean network-based analysis of the apoptosis network (Mai and Liu 2009) | |
| "To understand the design principles of the molecular interaction network associated with the irreversibility of cell apoptosis and the stability of cell surviving, we constructed a Boolean network integrating both the intrinsic and extrinsic pro-apoptotic pathways with pro-survival signal transduction pathways. We performed statistical analyses of the dependences of cell fate on initial states and on input signals. The analyses reproduced the well-known pro- and anti-apoptotic effects of key external signals and network components. We found that the external GF signal by itself did not change the apoptotic ratio from randomly chosen initial states when there is no external TNF signal, but can significantly offset apoptosis induced by the TNF signal. ..." | |
| Emergence of physiological oscillation frequencies in neocortex simulations (Neymotin et al. 2011) | |
| "Coordination of neocortical oscillations has been hypothesized to underlie the “binding” essential to cognitive function. However, the mechanisms that generate neocortical oscillations in physiological frequency bands remain unknown. We hypothesized that interlaminar relations in neocortex would provide multiple intermediate loops that would play particular roles in generating oscillations, adding different dynamics to the network. We simulated networks from sensory neocortex using 9 columns of event-driven rule-based neurons wired according to anatomical data and driven with random white-noise synaptic inputs. ..." | |
| Hopfield and Brody model (Hopfield, Brody 2000) (NEURON+python) | |
| Demonstration of Hopfield-Brody snychronization using artificial cells in NEURON+python. | |
| Ketamine disrupts theta modulation of gamma in a computer model of hippocampus (Neymotin et al 2011) | |
| "Abnormalities in oscillations have been suggested to play a role in schizophrenia. We studied theta-modulated gamma oscillations in a computer model of hippocampal CA3 in vivo with and without simulated application of ketamine, an NMDA receptor antagonist and psychotomimetic. Networks of 1200 multi-compartment neurons (pyramidal, basket and oriens-lacunosum moleculare, OLM, cells) generated theta and gamma oscillations from intrinsic network dynamics: basket cells primarily generated gamma and amplified theta, while OLM cells strongly contributed to theta. ..." | |
| Measuring neuronal identification quality in ensemble recordings (isoitools) (Neymotin et al. 2011) | |
| "... Here we describe information theoretic measures of action potential waveform isolation applicable to any dataset, that have an intuitive, universal interpretation, and that are not dependent on the methods or choice of parameters for single unit isolation, and that have been validated using a dataset." | |
| NEURON interfaces to MySQL and the SPUD feature extraction algorithm (Neymotin et al. 2007) | |
| See the readme.txt for information on setting up this interface to a MySQL server from the NEURON simulator. Note the SPUD feature extraction algorithm includes its own readme in the spud directory. | |
| Prosthetic electrostimulation for information flow repair in a neocortical simulation (Kerr 2012) | |
| This model is an extension of a model (138379) recently published in Frontiers in Computational Neuroscience. This model consists of 4700 event-driven, rule-based neurons, wired according to anatomical data, and driven by both white-noise synaptic inputs and a sensory signal recorded from a rat thalamus. Its purpose is to explore the effects of cortical damage, along with the repair of this damage via a neuroprosthesis. | |
| Reinforcement learning of targeted movement (Chadderdon et al. 2012) | |
| Synaptic information transfer in computer models of neocortical columns (Neymotin et al. 2010) | |
| "... We sought to measure how the activity of the network alters information flow from inputs to output patterns. Information handling by the network reflected the degree of internal connectivity. ... With greater connectivity strength, the recurrent network translated activity and information due to contribution of activity from intrinsic network dynamics. ... At still higher internal synaptic strength, the network corrupted the external information, producing a state where little external information came through. The association of increased information retrieved from the network with increased gamma power supports the notion of gamma oscillations playing a role in information processing." | |
| Synaptic scaling balances learning in a spiking model of neocortex (Rowan & Neymotin 2013) | |
| Learning in the brain requires complementary mechanisms: potentiation and activity-dependent homeostatic scaling. We introduce synaptic scaling to a biologically-realistic spiking model of neocortex which can learn changes in oscillatory rhythms using STDP, and show that scaling is necessary to balance both positive and negative changes in input from potentiation and atrophy. We discuss some of the issues that arise when considering synaptic scaling in such a model, and show that scaling regulates activity whilst allowing learning to remain unaltered. | |
| The virtual slice setup (Lytton et al. 2008) | |
| "In an effort to design a simulation environment that is more similar to that of neurophysiology, we introduce a virtual slice setup in the NEURON simulator. The virtual slice setup runs continuously and permits parameter changes, including changes to synaptic weights and time course and to intrinsic cell properties. The virtual slice setup permits shocks to be applied at chosen locations and activity to be sampled intra- or extracellularly from chosen locations. ..." | |
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